similar to: apply on logical data frame together with all (PR#6560)

Wrap your data frame in data.matrix() and you should be fine; e.g., apply(data.matrix(df), 1, all) Don't think this qualifies as bug... Andy > From: roland.puntaier@chello.at > > Full_Name: Roland Puntaier > Version: 1.8.1 > OS: Windows XP > Submission from: (NULL) (62.99.238.78) > > > I have a data frame with some columns being logical. > I wanted to

Wrap your data frame in data.matrix() and you should be fine; e.g., apply(data.matrix(df), 1, all) Don't think this qualifies as bug... Andy > From: roland.puntaier@chello.at > > Full_Name: Roland Puntaier > Version: 1.8.1 > OS: Windows XP > Submission from: (NULL) (62.99.238.78) > > > I have a data frame with some columns being logical. > I wanted to

Hi, I am relatively new to R; when creating functions, I run into problems with missing values. I would like my functions to ignore rows with missing values for arguments of my function) in the analysis (as for example is the case in STATA). Note that I don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my

I am working with some survival data with missing values. I am using the mice package to do multiple imputation. I have found code in this thread which handles pooling of the MI results: https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html Now I would like to plot a survival curve using the pooled results. Here is a reproducible example: require(survival) require(mice) set.seed(2) dt

Hi, I used to use reshape and moved to reshape2 (R 2.15.1). Now I tried some of my older scripts and was surprised that my cast function wasn't working like before. What I did/want to do: 1) Melt a dataframe based on a vector specifying column names as measure.vars. Thats working so far: dfm <- melt(df, measure.vars=n, variable_name = "species", na.rm = FALSE) 2) Recast the

Hi There, I get the following error from the code pasted below: Error in storage.mode(test) <- "logical" : object 'HGBmt12_Natl_Ave_or_Facility' not found library(RODBC) library(car) setwd("c://temp//cms") a07.connect <- odbcConnectAccess2007("DFC.accdb") sqlTables(a07.connect) ##provides list of tables## dataset <-

Hello, Have anybody a hint, how I could iterate over the vector below. So I'll wish only 8 iterations. Put the "range vector" in c() didn't help. for(i in c(1,2,3,4,5,11:20,21:50,51:100)) { sum(dfc[i,"cnt"]) # or similar actions } Thanks in advance Christian

Hello all, I really appreciate how helpful the people in this list are. Would it be too much to ask to send a small script to have it peer-reviewed? to make sure I am not making blatant mistakes? The script takes an experiment.dat as input and generates system Throughput using ggplot2. It works now ... [sigh] but I have this nasty feeling that I might be doing something wrong :). Changing

R-helpers: I have a dataset that has 168 subjects and 12 variables. Some of the variables have missing data and I want to use the multiple imputation capabilities of the "mice" package to address the missing data. Given that mice only supports linear models and generalized linear models (via the lm.mids and glm.mids functions) and that I need to fit Cox models, I followed the previous

I read in a CSV file with Data <- read.csv(file="FileName.csv",head=TRUE,sep=",") the file containts strings in the 2nd and 3rd columns and each has about 1000 rows. I need to either loop through the strings there looking for strings that would trigger other logic or remove those rows and put them in another array and loop through them in the new array. I can't seem

Hello, I would like to reshape a dataframe into an array. This is kind a similar task as Excel performs with a Pivot table. To illustrate it: LOC <- factor(c(1,2,2,3,1,1)) SPEC1 <- c(0,0,23,0,12,11) SPEC2 <- c(1,2,0,0,0,4) df <- data.frame(LOC,SPEC1,SPEC2) # original dataframe a <-

Package: logcheck-database Version: 1.2.37 Severity: normal Hello again, openntpd gives messages like these failry often: Apr 7 14:25:55 terminus ntpd[673]: peer 204.17.42.202 now invalid Apr 7 14:26:10 terminus ntpd[673]: peer 204.17.42.202 now valid I am not sure if this is something that an admin may find relevant but they happen fairly often and they do not offer a lot of info for me.

Package: logcheck-database Version: 1.2.36 Severity: wishlist Hello, I recently blew away my old logcheck-databse and lost a number of changes that i had made to postfix entries. The default database for postfix reports the following errors that do not seem to be important... Apr 2 13:00:19 terminus postfix/local[29516]: 574B9B3B9F: to=<doug at localhost>, relay=local, delay=13,

Hello (my machine is a Debian/Sid/x86-64/Core2) Assuming I have one C source file chello.c, to compile it into a dynamically loadable thru dlopen shared object, I can run gcc -fPIC -shared -O chello.c -o chello.so I thought that, assuming I have one llvm source ehello.ll, the equivalent would be llvmc2 -opt ehello.ll -o ehello.so but it is not that simple. Any clues ? May I also

I can't get anything to run using wine on my new laptop. I have slackware 9.1, kernel 2.6.0, and XFree86 4.4 RC2. I am running 2 programs on my desk top machine that won't run on the laptop. THe desktop has slackware 9.0, kernel 2.4.22 and XFree86 4.3.0. Can anybody help? Also the laptop has an installation of windows xp which is not found by the wineinstall script. Thanks, Tom

Dear All, I have these data: exampledata <- c("This is one item", "This is Another One", "And so is This") I would like to find each occurence of a blank space followed by a Capital Letter and replace it by a blank space, a left curly brace, the respective Capital Letter, and then a right curly brace. I thought the following will do: gsub(pattern = "

Hello R-experts, I am having difficulties with 3D plotting (i.e. the evolution of various forward curves through time). I have two comma seperated files both ordered by date (in the first column) one containing contracts (meaning forward delivery months from YEAR_ & Letter "F" ... January through letter "Z" ... December) and the other holding the closing price of the

Greetings everyone, I was wondering if anyone had experience in using fda (flexible discriminant analysis) in the mda package. Specifically, I can run the model but I cant locate/produce much of anything beyond the predicted values and confusion matrix. I've been searching for more examples or documentation but cant seem to locate any specific to the program itself. I need to be able to find

The limit parameter for SFQ qdiscs isn''t listed in the howto. Based on a mail from this list from 4 may 2002 ("SFQ queue lengths - generalization"), I''d guess it limits the number of packets/bytes in in the queue, but wether it does so by number of bytes, packets, or time spent in the queue I don''t know. Perhaps someone in the know could add a line to the

How do you call a javascript function to do something when the response is returned to the visitors browser? Easy ey? //Daniel -- Posted via http://www.ruby-forum.com/.